Summary

This mid-level data engineering role builds scalable data pipelines, architectures, and access solutions for investment banking data products. The stack includes Python, Databricks, SQL, AWS Glue, cloud data services, and AI-assisted software development; the working arrangement is not specified.

Responsibilities

• Develop etl workflows with Python and Databricks
• Build and maintain scalable data pipelines
• Review controls protecting enterprise data
• Implement data security and entitlements
• Update logical and physical data models
• Write complex SQL joins and aggregations
• Apply AI-assisted testing and development practices